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Ground states of three-dimensional EA Ising spin glasses are calculated for sizes up to 14^3 using a combination of a genetic algorithm and cluster-exact approximation. For each realization several independent ground states are obtained.…

Disordered Systems and Neural Networks · Physics 2015-06-25 Alexander K. Hartmann

We present an algorithm which calculates groundstates of Ising spin glasses approximately. It works by randomly selecting clusters of spins which exhibit no frustrations. The spins which were not selected, contribute to the local fields of…

Condensed Matter · Physics 2015-06-25 A. K. Hartmann

A huge number of independent true ground-state configurations is calculated for two-, three- and four-dimensional +- J spin-glass models. Using the genetic cluster-exact approximation method, system sizes up to N=20^2,8^3,6^4 spins are…

Disordered Systems and Neural Networks · Physics 2009-10-31 Alexander K. Hartmann

We employ a novel algorithm using a quasi-exact embedded-cluster matching technique as minimization method within a genetic algorithm to reliably obtain numerically exact ground states of the Edwards-Anderson XY spin glass model with…

Disordered Systems and Neural Networks · Physics 2007-05-23 Martin Weigel , Michel J. P. Gingras

Due to an extremely rugged structure of the free energy landscape, the determination of spin-glass ground states is among the hardest known optimization problems, found to be NP-hard in the most general case. Owing to the specific structure…

Disordered Systems and Neural Networks · Physics 2011-11-10 Martin Weigel

The use of combinatorial optimization algorithms has contributed substantially to the major progress that has occurred in recent years in the understanding of the physics of disordered systems, such as the random-field Ising model. While…

Disordered Systems and Neural Networks · Physics 2023-02-22 Manoj Kumar , Martin Weigel

We describe a numerical algorithm for computing spin glass ground states with a high level of reliability. The method uses a population based search and applies optimization on multiple scales. Benchmarks are given leading to estimates of…

Disordered Systems and Neural Networks · Physics 2009-11-07 Jerome Houdayer , Olivier C. Martin

A ``ballistic-search'' algorithm is presented which allows the identification of clusters (or funnels) of ground states in Ising spin glasses even for moderate system sizes. The clusters are defined to be sets of states, which are connected…

Disordered Systems and Neural Networks · Physics 2009-10-31 Alexander K. Hartmann

Using the discrete $\pm J$ bond distribution for the Sherrington-Kirkpatrick spin glass, all ground states for the entire ensemble of the bond disorder are enumerated. Although the combinatorial complexity of the enumeration severely…

Disordered Systems and Neural Networks · Physics 2007-05-23 Stefan Boettcher , Tomasz M. Kott

We analyze the zero-temperature behavior of the XY Edwards-Anderson spin glass model on a square lattice. A newly developed algorithm combining exact ground-state computations for Ising variables embedded into the planar spins with a…

Disordered Systems and Neural Networks · Physics 2007-05-23 Martin Weigel , Michel J. P. Gingras

Ground states of 3d EA Ising spin glasses are calculated for sizes up to $14^3$ using a combination of genetic algorithms and cluster-exact approximation . The distribution $P(|q|)$ of overlaps is calculated. For increasing size the width…

Disordered Systems and Neural Networks · Physics 2009-10-30 Alexander K. Hartmann

For many systems with quenched disorder the study of ground states can crucially contribute to a thorough understanding of the physics at play, be it for the critical behavior if that is governed by a zero-temperature fixed point or for…

Disordered Systems and Neural Networks · Physics 2020-06-12 Manoj Kumar , Martin Weigel

We compare the performance of extremal optimization (EO), flat-histogram and equal-hit algorithms for finding spin-glass ground states. The first-passage-times to a ground state are computed. At optimal parameter of tau=1.15, EO outperforms…

Statistical Mechanics · Physics 2009-11-07 Jian-Sheng Wang , Yutaka Okabe

This paper studies clustering algorithms for dynamically evolving graphs $\{G_t\}$, in which new edges (and potential new vertices) are added into a graph, and the underlying cluster structure of the graph can gradually change. The paper…

Data Structures and Algorithms · Computer Science 2024-06-06 Steinar Laenen , He Sun

Clustering is a difficult and widely-studied data mining task, with many varieties of clustering algorithms proposed in the literature. Nearly all algorithms use a similarity measure such as a distance metric (e.g. Euclidean distance) to…

Neural and Evolutionary Computing · Computer Science 2019-10-24 Andrew Lensen , Bing Xue , Mengjie Zhang

In simulations of some infinite range spin glass systems with finite connectivity, it is found that for any resonable computational time, the saturatedenergy per spin that is achieved by a cluster algorithm is lowered in comparison to that…

Condensed Matter · Physics 2016-08-31 N. Persky , I. Kanter , S. Solomon

Stellar streams that emerge from globular clusters (GCs) are thin stellar structures spread along the orbits of progenitor clusters. Numerical modeling of these streams is essential for understanding their interaction with the host galaxy's…

Astrophysics of Galaxies · Physics 2025-01-14 Yingtian Chen , Monica Valluri , Oleg Y. Gnedin , Neil Ash

Large numbers of ground states of two-dimensional Ising spin glasses with periodic boundary conditions in both directions are calculated for sizes up to 40^2. A combination of a genetic algorithm and Cluster-Exact Approximation is used. For…

Disordered Systems and Neural Networks · Physics 2009-10-31 Alexander K. Hartmann

We propose an extended genetic algorithm (GA) with different local environmental conditions. Genetic entities, or configurations, are put on nodes in a ring structure, and location-dependent environmental conditions are applied for each…

Data Analysis, Statistics and Probability · Physics 2022-06-22 Daekyung Lee , Beom Jun Kim

We describe a method for simulating and characterizing realistic Gottesman-Kitaev-Preskill (GKP) cluster states, rooted in the representation of resource states in terms of sums of Gaussian distributions in phase space. We apply our method…

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